2The operator of a pumping station has observed that demand for water during early afternoon hours has an approximately exponential distribution with mean 100 cfs (cubic feet per second).(a) Find the probability that the demand will exceed 250 cfs during the early afternoon on a randomly selected day. (Round your answer to four decimal places.)(b) What water-pumping capacity, in cubic feet per second, should the station maintain during early afternoons so that the probability that demand will exceed capacity on a randomly selected day is only 0.02?(Round your answer to two decimal places.)cfs

2) Given,The operator of a pumping station has observed that demand for water during early afternoon…

Answered: The operator of a pumping station has…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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Annual salaries in a large organization can be modeled as a lognormal variable with log (to the base 10) transformed mean of 4.4 and log (to the base 10) transformed standard deviation of 0.8. Find the salary that is exceeded by 65% of the employees.
15 The operator of a pumping station has observed that demand for water during early afternoon hours has an approximately exponential distribution with mean 100 cfs (cubic feet per second). (a) Find the probability that the demand will exceed 230 cfs during the early afternoon on a randomly selected day. (Round your answer to four decimal places.) (b) What water-pumping capacity, in cubic feet per second, should the station maintain during early afternoons so that the probability that demand will exceed capacity on a randomly selected day is only 0.02? (Round your answer to two decimal places.) cfs
On the basis of data collected from metal shredders across the nation, the amount x of extractable lead in metal shredder residue has an approximate exponential distribution with mean 0 = 2.5 milligrams per liter. Complete parts a and b. a. Find the probability that x is greater than 1.5 milligrams per liter. The probability is (Round to six decimal places as needed.)
A maintenance person has the job of keeping two machines in working order. The amount of time that a machine works before breaking down has an exponential distribution with a mean of 10 hours. The time then spent by the maintenance person repairing the machine has an exponential distribution with a mean of 8 hours. A. Show that this process fits the birth-and-death process by defining the states, specifying the values of the λn and μn, and then constructing the rate diagram. (Hint: Let the state represent the number of machines that are broken down). B. Calculate the Pn. C. Calculate L, Lq, W, and Wq. D. Determine the proportion of time that the maintenance person is busy. E. Determine the proportion of time that any given machine is working. Need the excel formula, if necessary
The time (in years) after reaching age 60 that it takes an individual to retire is approximately exponentially distributed with a mean of about 7 years. Suppose we randomly pick one retired individual. We are interested in the time after age 60 to retirement. In a room of 1,000 people over age 81, how many do you expect will NOT have retired yet? (Round your answer to the nearest whole number.)
A safety engineer uses simple logistic regression tostudy the relationship between occupancy years (x)and evacuation decision (y), under a majorhurricane forecast. Each occupant willevacuate (Y = 1) or stay (Y = 0). Sample dataprovides the estimated logit function:w = 2.83 − 0.24x. Estimate the odds that ahomeowner of 10 years will evacuate.
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John bought a second-hand car that was driven 16 kilometers (km) from sahibindenmiacaba.com. What is the probability that he will be able to drive this car at least for another 20 km before it has to be salvaged if life of a car (in km) is exponentially distributed with a rate parameter of 1/30? Answer uniformly distributed over (0, 140)? Answer
Read the question carefully and give me both a&b right solution according to the question. A catalyst powder has the following weight distribution in the given particle size range: 10-20 µm, 10.0 %; 20-30 µm, 42.0 %; 30-40 µm, 33.0 %; 40-50 µm. 9.0 %; 50-80 µm, 5.9 %. From a log-probability plot estimate (a) the geometric mean diameter, (b) the standard deviation of that mean diameter.
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